RozaMira gas stations increased fuel realization up to 26% by clients who have falling demand

A personal price for fuel was formed for clients with falling demand. The result was achieved after 2 weeks of using the service.
Business scale and background: The company RozaMira has 15 gas stations. Due to the limited local market, the tasks of retaining the existing clients base come to the fore.
Tasks: ensuring the return of lost customers at the expense of personal fuel prices, as well as increasing their average check through individual offers for related products.
Solution: integration to the Mega Insight platform and the launch of a new mobile application that allows to form individual price proposals for fuel and goods for clients with advanced analytics by them.
Results: monitoring of the condition of clients allowed us to give a low price only to customers focused on it and, as a result, to keep sufficiently high prices for the stele. This approach maintains overall margins without falling sales volumes.
Service Megainsight began to give a stable result within 2 weeks after the start of use, which is confirmed by smiles and positive feedback from our clients at the gas station cash desks.
As practice shows, the times of loyalty bonus programs are gradually passing, so our main task was to "hook" new drivers of our city, and this solution was found. Until the introduction of the Megainsight service, we did not work with our existing, relatively large, customer base and now we have a fully digitalized base, we build various consumption hypotheses and, as a result, each of our client receives an individual price for fuel and coffee. Thus, we constantly warm up our visitors and stand out against the background of other gas station chains, which was the main task of the company.
Konstantin Goncharov
Board member
Key benefits:
According to the internal report of customer and the data of Megainsight

increased fuel realization by clients
who have falling demand.

increase in sales of coffee drinks in the summer. Growth instead of seasonal decline!
in 2 times

increased weekly gain of new clients due to the ability to share coupons to friends.
For the analysis, we took the indicators for May-June 2021. As a result, the RozaMira gas station network was fully pay off the funds invested in the platform only on the basis of the growth in coffee sales. The rest of the sales growth is a plus!
Key cases of platform application in customer:
Case 1. Return of frequent clients with falling demand
A detailed analysis of the consumption model of each client made it possible to form a number of parameters, on the basis of which it became possible to create target groups for clients whose demand is falling at the moment. In addition, the most demanded customers were determined among them by the monthly number of visited thr gas stations, the average bill and other parameters. This allowed us to single out a narrow group, influencing which the Company can get the maximum effect. Then, for the formed group, a coupon was sent to the application with a personal price for gasoline. Conversion for such coupons averaged 20%, and instead of falling demand for these customers, growth began.
Case 2. Increase in sales of coffee drinks
As in case № 1, the first step was to form target groups by consumption parameters. However, this time the target groups of clients were determined by those who had never bought coffee drinks. It was hypothesized that a price-driven customer does not buy coffee at a gas station. For such customers, a coupon was created for coffee drinks with a special personal price reduced by 20-30%. As a result, in 30 days such clients managed to sell about 600 cups of coffee. At the same time, for those who previously bought coffee, the price has not changed. Those. RosaMira sold 600 more in a month, and this is in the summer. In autumn and winter, it is assumed that the sales volume will be 2-3 times higher than usual.
Case 3. Who likes to buy goods
In this case, the functionality of automatic calculation of recommendations for each client of the gas station was used. A list of coupons for the most popular items of goods with prices reduced by 10-15% was created in advance. Machine learning algorithms made it possible for each client to form its own unique list of coupons, based on the purchase history of both the client himself and others similar to him in terms of the consumption model. Thus, each client automatically receives a truly personalized set of offers, which allows them to increase conversions by up to 40%.
What's become available due to Megainsight:
Data collection and customer segmentation
Creation of a single place for storing and processing all client data, followed by deduplication and normalization. Convenient interface for forming target customer groups by consumption parameters for a task or hypothesis, depending on the needs of the company.
Target offers and prices
Flexible functionality for creating holding shares in the form of coupons that can be linked both to a specific group of clients and individually to each client, depending on recommendations from machine intelligence.
Attracting new customers through sharing
All individual offers in the mobile application can be shared with friends. If you received an individual price for fuel or goods, you can share it with a friend. Thus, friends immediately get into the loyalty system and come to the gas station.
Branded mobile app for clients
A completely updated mobile application that allows to conduct personal communication with the client and increase his brand loyalty through gamification and personal discounts.
Conversion control
The ability to track key business metrics and their dynamics of changes for each target group of customers formed in the platform.
Hierarchical pricing
Transparent ROI analysis for each price coupon, which allows you to form a client group among those who used it / did not use it for further impact and increase the conversion to sale.
SIA "Megainsight"
26a, Ganibu dambi, Riga, Latvia LV-1005
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